1. Technical Field
The present disclosure relates generally to the highly sensitive quantification of the relative representation of adaptive immune cells in complex mixtures of cells using multiplex digital polymerase chain reaction (dPCR) or multiplex quantitative polymerase chain reaction (qPCR). In particular, the present disclosure relates to methods for quantitative determination of lymphocyte presence in complex tissues including solid tissues, such as quantification of tumor-infiltrating lymphocyte (TIL) genomes as a relative proportion of all cellular genomes that are represented in a tumor DNA sample, or quantification of the genomes of lymphocytes that have infiltrated somatic tissue in the pathogenesis of inflammation, allergy or autoimmune disease or in transplanted organs as a relative proportion of all cellular genomes that are represented in a tissue DNA sample.
2. Description of the Related Art
The adaptive immune system protects higher organisms against infections and other pathological events that may be attributable to foreign substances, using adaptive immune receptors, the antigen-specific recognition proteins that are expressed by hematopoietic cells of the lymphoid lineage and that are capable of distinguishing self from non-self molecules in the host. These lymphocytes may be found in the circulation and tissues of a host, and their recirculation between blood and the lymphatics has been described, including their extravasation via lymph node high endothelial venules, as well as at sites of infection, inflammation, tissue injury and other clinical insults. (See, e.g., Stein et al., 2005 Immunol. 116:1-12; DeNucci et al., 2009 Crit. Rev. Immunol. 29:87-109; Marelli-Berg et al., 2010 Immunol. 130:158; Ward et al., 2009 Biochem. J. 418:13; Gonzalez et al., 2011 Ann. Rev. Immunol. 29:215; Kehrl et al., 2009 Curr. Top. Microb. Immunol. 334:107; Steinmetz et al., 2009 Front. Biosci. (Schol. Ed.) 1:13.)
Accordingly, the dynamic nature of movement by lymphocytes throughout a host organism is reflected in changes in the qualitative (e.g., antigen-specificity of the clonally expressed adaptive immune receptor (immunoglobulin or T cell receptor), T cell versus B cell, T helper (Th) cell versus T regulatory (Treg) cell, effector T cell versus memory T cell, etc.) and quantitative distribution of lymphocytes among tissues, as a function of changes in host immune status.
For example, numerous studies have found an association between (i) the presence of tumor infiltrating lymphocytes (TIL) in a variety of solid tumors and (ii) patient prognosis and overall survival rates. In some studies, tumor infiltrating T cells having a specific phenotype (e.g., CD8+ and CD4+ T cells or regulatory T cells) are positive or negative predictors of survival (e.g., Jochems et al., 2011 Experimental Biol. Med. 236:567-579). In certain cases, however, TIL count alone is a predictor of long-term survival (e.g., Katz et al., 2009 Ann. Surg. Oncol. 16:2524-2530). Thus, quantitative determination of TIL counts has high prognostic value in a variety of cancers including colorectal, hepatocellular, gallbladder, pancreatic, esophageal, ovarian endometrial, cervical, bladder and urothelial cancers. While more is known about the association of tumor-infiltrating T cells, B cells are also known to infiltrate tumors and studies have shown an association of tumor-infiltrating B cells with survival advantage (e.g., Ladányi, et al., Cancer Immunol. Immunother. 60(12):1729-38, Jul. 21, 2011 (epub ahead of print).
The quantitative determination of the presence of adaptive immune cells (e.g., T and B lymphocytes) in diseased tissues may therefore provide useful information for diagnostic, prognostic and other purposes, such as in cancer, infection, inflammation, tissue injury and other conditions.
The adaptive immune system employs several strategies to generate a repertoire of T- and B-cell antigen receptors with sufficient diversity to recognize the universe of potential pathogens. B lymphocytes mature to express antibodies (immunoglobulins, Igs) that occur as heterodimers of a heavy (H) a light (L) chain polypeptide, while T lymphocytes express heterodimeric T cell receptors (TCR). The ability of T cells to recognize the universe of antigens associated with various cancers or infectious organisms is conferred by its T cell antigen receptor (TCR), which is made up of both an α (alpha) chain and a β (beta) chain or a γ (gamma) and a δ (delta) chain. The proteins which make up these chains are encoded by DNA, which employs a unique mechanism for generating the tremendous diversity of the TCR. This multi-subunit immune recognition receptor associates with the CD3 complex and binds to peptides presented by the major histocompatibility complex (MHC) class I and II proteins on the surface of antigen-presenting cells (APCs). Binding of TCR to the antigenic peptide on the APC is the central event in T cell activation, which occurs at an immunological synapse at the point of contact between the T cell and the APC.
Each TCR peptide contains variable complementarity determining regions (CDRs), as well as framework regions (FRs) and a constant region. The sequence diversity of αβ T cells is largely determined by the amino acid sequence of the third complementarity-determining region (CDR3) loops of the α and β chain variable domains, which diversity is a result of recombination between variable (Vβ), diversity (Dβ, and joining (Jβ) gene segments in the β chain locus, and between analogous Vα and Jα gene segments in the α chain locus, respectively. The existence of multiple such gene segments in the TCR α and β chain loci allows for a large number of distinct CDR3 sequences to be encoded. CDR3 sequence diversity is further increased by independent addition and deletion of nucleotides at the Vβ-Dβ, Dβ-Jβ, and Vα-Jα junctions during the process of TCR gene rearrangement. In this respect, immunocompetence is reflected in the diversity of TCRs.
The γδ TCR is distinctive from the αβ TCR in that it encodes a receptor that interacts closely with the innate immune system. TCRγδ, is expressed early in development, has specialized anatomical distribution, has unique pathogen and small-molecule specificities, and has a broad spectrum of innate and adaptive cellular interactions. A biased pattern of TCRγ V and J segment expression is established early in ontogeny as the restricted subsets of TCRγδ cells populate the mouth, skin, gut, vagina, and lungs prenatally. Consequently, the diverse TCRγ repertoire in adult tissues is the result of extensive peripheral expansion following stimulation by environmental exposure to pathogens and toxic molecules.
Igs expressed by B cells are proteins consisting of four polypeptide chains, two heavy chains (H chains) and two light chains (L chains), forming an H2L2 structure. Each pair of H and L chains contains a hypervariable domain, consisting of a VL and a VH region, and a constant domain. The H chains of Igs are of several types, μ, δ, γ, α, and β. The diversity of Igs within an individual is mainly determined by the hypervariable domain. Similar to the TCR, the V domain of H chains is created by the combinatorial joining of the VH, DH, and JH gene segments. Hypervariable domain sequence diversity is further increased by independent addition and deletion of nucleotides at the VH-DH, DH-JH, and VH-JH junctions during the process of Ig gene rearrangement. In this respect, immunocompetence is reflected in the diversity of Igs.
Quantitative characterization of adaptive immune cells based on the presence in such cells of functionally rearranged Ig and TCR encoding genes that direct productive expression of adaptive immune receptors has been achieved using biological samples from which adaptive immune cells can be readily isolated in significant numbers, such as blood, lymph or other biological fluids. In these samples, adaptive immune cells occur as particles in fluid suspension. See, e.g., US 2010/0330571; see also, e.g., Murphy, Janeway's Immunobiology (8th Ed.), 2011 Garland Science, NY, Appendix I, pp. 717-762.
Current approaches to the detection and quantification of adaptive immune cells in tissues or organs from which adaptive immune cells cannot be readily isolated, however, are far more limited. For example, in solid tissues and solid tumors, adaptive immune cell detection typically requires histological detection in a small, non-representative sample such as a fixed or frozen section of a biopsy specimen, using laborious and at most semi-quantitative techniques such as immunohistochemistry or in situ hybridization (e.g., Bancroft and Gamble, Theory and Practice of Histological Techniques, Churchill Livingstone, 2007; Carson and Hladik, Histotechnology: A Self-Instructional Text, 2009 Am. Soc. Clin. Pathol.). In conventional practice, the excised tissue may be cut into a plurality of serial histological sections along substantially parallel planes, for analysis by any of a number of known histological, histochemical, immunohistological, histopathologic, microscopic (including morphometric analysis and/or three-dimensional reconstruction), cytological, biochemical, pharmacological, molecular biological, immunochemical, imaging or other analytical techniques, which techniques are known to persons skilled in the relevant art. See, e.g., Bancroft and Gamble, Theory and Practice of Histological Techniques (6th Ed.), 2007 Churchill Livingstone, Oxford, UK; Kiernan, Histological and Histochemical Methods: Theory and Practice, 2001 Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y.; M. A. Hayat (Ed.), Cancer Imaging-Vols. 1 and 2, 2007 Academic Press, NY.
Efforts to obtain meaningful quantitative data from such approaches are severely limited with regard to the number of adaptive immune cells that may have infiltrated a tissue, for instance, where high statistical significance cannot be achieved when sample collection depends on the number of events that can be detected by observation of a finite number of small fields on microscope slides. Alternatively, a tissue sample must be mechanically and/or enzymatically dissociated to produce a single-cell suspension that is amenable to flow immunocytofluorimetric analysis (e.g., Murphy, 2011, pp. 740-742), although such time-consuming and labor-intensive steps are likely to result in incomplete recovery of lymphocytes from the sample due to loss or destruction of a portion of the sample in the course of handling. These and related limitations of the current approaches compromise the quality of quantitative data that may be obtained.
Clearly there is a need for an improved method for quantifying adaptive immune cells in a complex biological sample containing a mixture of cells that are not all adaptive immune cells, without requiring the isolation of adaptive immune cells from the sample, e.g., without having to separate the adaptive immune cells from the non-adaptive immune cells. The presently described embodiments address this need and offer other related advantages.